tfmot.quantization.keras.quantize_scope
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Scope which can be used to deserialize quantized Keras models and layers.
tfmot.quantization.keras.quantize_scope(
*args
)
Used in the notebooks
Under quantize_scope
, Keras methods such as tf.keras.load_model
and
tf.keras.models.model_from_config
will be able to deserialize Keras models
and layers which contain quantization classes such as QuantizeConfig
and Quantizer
.
Example:
tf.keras.models.save_model(quantized_model, keras_file)
with quantize_scope():
loaded_model = tf.keras.models.load_model(keras_file)
# If your quantized model uses custom objects such as a specific `Quantizer`,
# you can pass them to quantize_scope to deserialize your model.
with quantize_scope({'FixedRangeQuantizer', FixedRangeQuantizer}
loaded_model = tf.keras.models.load_model(keras_file)
For further understanding, see tf.keras.utils.custom_object_scope
.
Args |
*args
|
Variable length list of dictionaries of {name, class} pairs to add
to the scope created by this method.
|
Returns |
Object of type CustomObjectScope with quantization objects included.
|
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Last updated 2023-05-26 UTC.
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